Python Social Media Analytics
by Siddhartha Chatterjee and Michal Krystyanczuk
pages 页数：312 pages
Publisher Finelybook 出版社：Packt Publishing (4 Aug. 2017)
Leverage the power of Python to collect, process, and mine deep insights from social media data
About This Book
Acquire data from various social media platforms such as Facebook, Twitter, YouTube, GitHub, and more
Analyze and extract actionable insights from your social data using various Python tools
A highly practical guide to conducting efficient social media analytics at scale
Who This Book Is For
If you are a programmer or a data analyst familiar with the Python programming language and want to perform analyses of your social data to acquire valuable business insights, this book is for you. The book does not assume any prior knowledge of any data analysis tool or process.
What You Will Learn
Understand the basics of social media mining
Use PyMongo to clean, store, and access data in MongoDB
Understand user reactions and emotion detection on Facebook
Perform Twitter sentiment analysis and entity recognition using Python
Analyze video and campaign performance on YouTube
Mine popular trends on GitHub and predict the next big technology
Extract conversational topics on public internet forums
Analyze user interests on Pinterest
Perform large-scale social media analytics on the cloud
Social Media platforms such as Facebook, Twitter, Forums, Pinterest, and YouTube have become part of everyday life in a big way. However, these complex and noisy data streams pose a potent challenge to everyone when it comes to harnessing them properly and benefiting from them. This book will introduce you to the concept of social media analytics, and how you can leverage its capabilities to empower your business.
Right from acquiring data from various social networking sources such as Twitter, Facebook, YouTube, Pinterest, and social forums, you will see how to clean data and make it ready for analytical operations using various Python APIs. This book explains how to structure the clean data obtained and store in MongoDB using PyMongo. You will also perform web scraping and visualize data using Scrappy and Beautifulsoup.
Finally, you will be introduced to different techniques to perform analytics at scale for your social data on the cloud, using Python and Spark. By the end of this book, you will be able to utilize the power of Python to gain valuable insights from social media data and use them to enhance your business processes.
Style and approach
This book follows a step-by-step approach to teach readers the concepts of social media analytics using the Python programming language. To explain various data analysis processes, real-world datasets are used wherever required.
Chapter 1. Introduction To The Latest Social Media Landscape And Importance
Chapter 2. Harnessing Social Data – Connecting, Capturing, And Cleaning
Chapter 3. Uncovering Brand Activity, Popularity, And Emotions On Facebook
Chapter 4. Analyzing Twitter Using Sentiment Analysis And Entity Recognition
Chapter 5. Campaigns And Consumer Reaction Analytics On Youtube – Structured And Unstructured
Chapter 6. The Next Great Technology – Trends Mining On Github
Chapter 7. Scraping And Extracting Conversational Topics On Internet Forums
Chapter 8. Demystifying Pinterest Through Network Analysis Of Users Interests
Chapter 9. Social Data Analytics At Scale – Spark And Amazon Web Services
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